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(Image from https://github.com/IDEA-Research/Grounded-Segment-Anything/blob/main/assets/demo7.jpg)
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Horse. Clouds. Grasses. Sky. Hill.
This model requires additional module.
pip3 install ailia_tokenizer
Automatically downloads the onnx and prototxt files on the first run. It is necessary to be connected to the Internet while downloading.
For the sample image,
$ python3 groundingdino.py
If you want to specify the input image, put the image path after the --input
option.
You can use --savepath
option to change the name of the output file to save.
$ python3 groundingdino.py --input IMAGE_PATH --savepath SAVE_IMAGE_PATH
If you want to specify the caption for detection, put the caption after the --caption
option.
If you want to detect multiple objects in one sentence, we suggest separating each name with .
.
An example: cat. dog. chair.
$ python3 groundingdino.py --caption "Horse. Clouds. Grasses. Sky. Hill."
Pytorch
ONNX opset=17